4,643 research outputs found
Parameter identification of dynamical systems from time series
No full textIn this paper, synchronization based parameter identification of dynamical systems from time series is carefully revisited. It is shown, based on rigorous theoretical analysis and concrete counterexamples, that some recent research reports on this issue are incomplete or even incorrect. A linear independence condition is pointed out, which is sufficient for such parameter identification of general dynamical systems
Tipping prediction of a class of large-scale radial-ring neural networks
No full textUnderstanding the emergence and evolution of collective dynamics in large-scale neural networks remains a complex challenge. This paper seeks to address this gap by applying dynamical systems theory, with a particular focus on tipping mechanisms. First, we introduce a novel ( n + mn )-scale radial-ring neural network and employ Coates' flow graph topological approach to derive the characteristic equation of the linearized network. Second, through deriving stability conditions and predicting the tipping point using an algebraic approach based on the integral element concept, we identify critical factors such as the synaptic transmission delay, the self-feedback coefficient, and the network topology. Finally, we validate the methodology's effectiveness in predicting the tipping point. The findings reveal that increased synaptic transmission delay can induce and amplify periodic oscillations. Additionally, the self-feedback coefficient and the network topology influence the onset of tipping points. Moreover, the selection of activation function impacts both the number of equilibrium solutions and the convergence speed of the neural network. Lastly, we demonstrate that the proposed large-scale radial-ring neural network exhibits stronger robustness compared to lower-scale networks with a single topology. The results provide a comprehensive depiction of the dynamics observed in large-scale neural networks under the influence of various factor combinations
Ruoxia Li, Jinde Cao, Ahmad Alsaedi, Fuad Alsaadi Stability analysis of fractional-order delayed neural networks
No full textAt the beginning, a class of fractional-order delayed neural networks were employed. It is known that the active functions in a target model may be Lipschitz continuous, while some others may also possessing inverse Lipschitz properties. Based upon the topological degree theory, nonsmooth analysis, as well as nonlinear measure method, several novel sufficient conditions are established towards the existence as well as uniqueness of the equilibrium point, which are voiced in terms of linear matrix inequalities (LMIs). Furthermore, the stability analysis is also attached. One numerical example and its simulations are presented to illustrate the theoretical findings
Robust H∞ feedback control for uncertain stochastic delayed genetic regulatory networks with additive and multiplicative noise
No full textThe official published version can found at the link below.Noises are ubiquitous in genetic regulatory networks (GRNs). Gene regulation is inherently a stochastic process because of intrinsic and extrinsic noises that cause kinetic parameter variations and basal rate disturbance. Time delays are usually inevitable due to different biochemical reactions in such GRNs. In this paper, a delayed stochastic model with additive and multiplicative noises is utilized to describe stochastic GRNs. A feedback gene controller design scheme is proposed to guarantee that the GRN is mean-square asymptotically stable with noise attenuation, where the structure of the controllers can be specified according to engineering requirements. By applying control theory and mathematical tools, the analytical solution to the control design problem is given, which helps to provide some insight into synthetic biology and systems biology. The control scheme is employed in a three-gene network to illustrate the applicability and usefulness of the design.This work was funded by Royal Society of the U.K.; Foundation for the Author of National Excellent Doctoral Dissertation of China. Grant Number: 2007E4; Heilongjiang Outstanding Youth Science Fund of China. Grant Number: JC200809; Fok Ying Tung Education Foundation. Grant Number: 111064; International Science and Technology Cooperation Project of China. Grant Number: 2009DFA32050; University of Science and Technology of China Graduate Innovative Foundation
Combined Heat and Power Dynamic Economic Dispatch with Emission Limitations Using Hybrid DE-SQP Method
No full textCombined heat and power dynamic economic emission dispatch (CHPDEED) problem is
a complicated nonlinear constrained multiobjective optimization problem with nonconvex
characteristics. CHPDEED determines the optimal heat and power schedule of committed
generating units by minimizing both fuel cost and emission simultaneously under ramp rate
constraints and other constraints. This paper proposes hybrid differential evolution (DE) and
sequential quadratic programming (SQP) to solve the CHPDEED problem with nonsmooth and
nonconvex cost function due to valve point effects. DE is used as a global optimizer, and SQP
is used as a fine tuning to determine the optimal solution at the final. The proposed hybrid
DE-SQP method has been tested and compared to demonstrate its effectiveness
Effect of CaO content in raw material on the mineral composition of ferric-rich sulfoaluminate clinker
No full textFerric-rich calcium sulfoaluminate (FR-CSA) cement is an eco-friendly cement. Fe2O3 exists in different minerals of FR-CSA clinker, e.g., Ca4Al2Fe2O10 (C4AF), Ca2Fe2O5 (C2F), and Ca4Al6-2xFe2xSO16 (C4A3-xFxS-). The mineral composition depends on the chemical composition of the raw materials and significantly determines the reactivity of FR-CSA cement. To optimize the phase composition of the FR-CSA clinker, chemical reagent raw mixtures with different amounts of CaO were used to prepare the FR-CSA clinker. X-ray diffraction (XRD) analysis, Rietveld quantitative phase analysis (RQPA), Fourier Transform Infrared spectroscopy (FT-IR), and scanning electron microscopy/energy-dispersive spectroscopy (SEM/EDS) were used to identify the mineralogical conditions of the FR-CSA clinker. The results indicated that the amounts of CaO in raw materials greatly affected the iron-bearing phase formation in the FR-CSA clinker. With decreasing CaO content involved in calcination reaction, the amounts of Fe2O3 incorporated in C4A3-xFxS- increased up to 17.72 wt% (where x = 0.36). The findings make it possible to optimize the mineral composition of the FR-CSA clinker by changing the CaO content in raw materials. Furthermore, low CaO content in the raw material is beneficial to the formation of C4A3-xFxS-, which enables the use of solid wastes containing low calcium for producing FR-CSA cement.Accepted author manuscriptMaterials and Environmen
Consensus in high-power multiagent systems with mixed unknown control directions via hybrid Nussbaum-based control
No full textThis work investigates the consensus tracking problem for high-power nonlinear multiagent systems with partially unknown control directions. The main challenge of considering such dynamics lies in the fact that their linearized dynamics contain uncontrollable modes, making the standard backstepping technique fail; also, the presence of mixed unknown control directions (some being known and some being unknown) requires a piecewise Nussbaum function that exploits the a priori knowledge of the known control directions. The piecewise Nussbaum function technique leaves some open problems, such as Can the technique handle multiagent dynamics beyond the standard backstepping procedure? and Can the technique handle more than one control direction for each agent? In this work, we propose a hybrid Nussbaum technique that can handle uncertain agents with high-power dynamics where the backstepping procedure fails, with nonsmooth behaviors (switching and quantization), and with multiple unknown control directions for each agent.Accepted Author ManuscriptTeam Bart De Schutte
Distributed Adaptive Consensus Disturbance Rejection: a Directed-spanning-tree Perspective
No full textIn this paper, we revisit the problem of consensus disturbance rejection for multiagent systems over a digraph, but from a different perspective, i.e., the perspective of a directed spanning tree (DST). When the minimum nonzero real part of the Laplacian eigenvalues is available, we reproduce the sufficient lower bound for a static homogeneous coupling gain in the literature, by exploring a DST structure of the digraph. The major novelty arises when it is shown that by adaptively tuning the coupling gains along a DST, consensus disturbance rejection can be achieved when the above eigenvalue information is not available. Numerical examples on networks of second-order oscillators and UAVs are included to validate the theoretical results. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Bart De Schutte
A Separation-Based Methodology to Consensus Tracking of Switched High-Order Nonlinear Multiagent Systems
No full textThis work investigates a reduced-complexity adaptive methodology to consensus tracking for a team of uncertain high-order nonlinear systems with switched (possibly asynchronous) dynamics. It is well known that high-order nonlinear systems are intrinsically challenging as feedback linearization and backstepping methods successfully developed for low-order systems fail to work. Even the adding-one-power-integrator methodology, well explored for the single-agent high-order case, presents some complexity issues and is unsuited for distributed control. At the core of the proposed distributed methodology is a newly proposed definition for separable functions: this definition allows the formulation of a separation-based lemma to handle the high-order terms with reduced complexity in the control design. Complexity is reduced in a twofold sense: the control gain of each virtual control law does not have to be incorporated in the next virtual control law iteratively, thus leading to a simpler expression of the control laws; the power of the virtual and actual control laws increases only proportionally (rather than exponentially) with the order of the systems, dramatically reducing high-gain issues.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Bart De Schutte
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